Anonymous.The high accuracy for both small and large motion estimation are mainly cause by two contributions: firstly, we present and implement an edge preserve patch match (EPM) layer that propagates self-similarity patterns in addition to offsets. The accuracy of optical flow prediction has greatly improved by this method. Secondly, we develop a course-to-fine network architecture to tackle large displacement estimation and introduce a residual flow method to solve small displacement estimation.

Anonymous.It is a well-known model that uses TV-L1 (coupled) as the regularization term and an L1 data term.

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UFO

Anonymous.We propose a framework for unsupervised learning of optical flow and occlusions over multiple frames. We exploit the minimal configuration of three frames to strengthen the photometric loss and explicitly reason about occlusions.